When querying data in Google BigQuery using the Python client library, the result is returned as a RowIterator object. While this is efficient for streaming results, most data scientists and engineers prefer working with Pandas DataFrames for further analysis.
pip install google-cloud-bigquery pandas
from google.cloud import bigquery import pandas as pd # Initialize BigQuery client client = bigquery.Client() # Example query query = "SELECT name, age FROM `project.dataset.table`" query_job = client.query(query) # This gives you a RowIterator row_iterator = query_job.result() # Convert to DataFrame df = row_iterator.to_dataframe() print(df.head())
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